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Asymptotic confidence intervals of location parameters are proposed in oneand two-sample models. These are robust procedures based on scale-invariant Mstatistics. The one-sample procedures have the same robustness as Huber’s Mestimators. Furthermore although the symmetry of the underlying distribution is needed in the asymptotic theory of Huber’s M-estimators,the proposed procedures do not demand the symmetry in the two-sample model. The asymptotic efficiency of the proposed confidence intervals is given by a numerical integration.

Asymptotic Confidence Intervals Based on M-procedures in One- and Two-sample Models